Looking Backward to Move Forward: Early Detection of Neurodegenerative Disorders

Dopamine in the prefrontal cortex plays multiple roles in the executive function of patients with Parkinson's disease

Parkinson's disease can affect not only motor functions but also cognitive abilities, leading to cognitive impairment. One common issue in Parkinson's disease with cognitive dysfunction is the difficulty in executive functioning. Executive functions help us plan, organize, and control our actions based on our goals. The brain area responsible for executive functions is called the prefrontal cortex. It acts as the command center for the brain, especially when it comes to regulating executive functions. The role of the prefrontal cortex in cognitive processes is influenced by a chemical messenger called dopamine. However, little is known about how dopamine affects the cognitive functions of patients with Parkinson's disease. In this article, the authors review the latest research on this topic. They start by looking at how the dopaminergic system, is altered in Parkinson's disease with executive dysfunction. Then, they explore how these changes in dopamine impact the synaptic structure, electrical activity, and connection components of the prefrontal cortex. The authors also summarize the relationship between Parkinson's disease and dopamine-related cognitive issues. This information may offer valuable insights and directions for further research and improvement in the clinical treatment of cognitive impairment in Parkinson's disease.

Influence of daily life and health profile in subtle cognitive decline of women residing in Spanish religious communities: DeCo religious orders study

Background

Prior to the onset of dementia, individuals commonly undergo a phase marked by subtle cognitive changes, known as subtle cognitive decline. Recognizing these early cognitive alterations is crucial, as they can serve as indicators of an impending decline in cognitive function, warranting timely intervention and support.

Objectives

To determine the incidence of subtle cognitive decline in a population of Spanish women and establish the relationship with possible protective and/or risk factors such as cognitive reserve, cardiovascular risk factors, medication consumption and psychosocial factors.

Design and participants

This is a cross-sectional observational study with women from the general population and a more homogeneous population composed of nuns from the Valencian region (Spain).

Measurements

A validated questionnaire was used including lifestyle variables, chronic illnesses, level of education and pharmacological treatments. Three validated subtle cognitive decline screening tests with varying levels of sensitivity and specificity were used: Memory Impairment Screening, Pfeiffer's Short Portable Mental State Questionnaire, and Semantic Verbal Fluency.

Results

Our results suggest that nuns may have a significantly reduced risk of cognitive decline compared to the general population (20.67% in nuns vs. 36.63% in the general population). This lower risk for subtle cognitive decline in nuns may be partly attributed to their higher cognitive reserve and long-time engagement in intellectually stimulating activities. Additionally, nuns tend to adopt healthy lifestyles, they are not isolated because they live in community and obtained lower scores for risk factors such as depression, anticholinergic burden, and benzodiazepine consumption.

Conclusion

A healthy lifestyle combined with intellectually stimulating activities is related with preserved cognitive function.

Salivary biomarkers: The early diagnosis of Alzheimer's disease

The precise identification of Alzheimer's disease and other prevalent neurodegenerative diseases remains a difficult issue that requires the development of early detection of the disease and inexpensive biomarkers that can replace the present cerebrospinal fluid and imaging biomarkers. Blood biomarkers, such as amyloid and neurofilament light, have been emphasized as an important and practical tool in a testing or examination procedure thanks to advancements in ultra-sensitive detection techniques. Although saliva is not currently being researched for neurodegenerative diseases, it is an important source of biomarkers that can be used for the identification of diseases and has some advantages over other biofluids. While this may be true for most people, getting saliva from elderly people presents some significant challenges. In this overview, we will first discuss how saliva is created and how aging-related illnesses may affect the amount and kind of saliva produced. The findings support the use of salivary amyloid protein, tau species, and novel biomarkers in the diagnosis of Alzheimer's disease.

The potential roles of salivary biomarkers in neurodegenerative diseases

Current research efforts on neurodegenerative diseases are focused on identifying novel and reliable biomarkers for early diagnosis and insight into disease progression. Salivary analysis is gaining increasing interest as a promising source of biomarkers and matrices for measuring neurodegenerative diseases. Saliva collection offers multiple advantages over the currently detected biofluids as it is easily accessible, non-invasive, and repeatable, allowing early diagnosis and timely treatment of the diseases. Here, we review the existing findings on salivary biomarkers and address the potential value in diagnosing neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. Based on the available research, β-amyloid, tau protein, α-synuclein, DJ-1, Huntington protein in saliva profiles display reliability and validity as the biomarkers of neurodegenerative diseases.

Brain atrophy in normal older adult links tooth loss and diet changes to future cognitive decline

Several studies have found associations between poor oral health, particularly tooth loss and cognitive decline. However, the specific brain regions affected by tooth loss and the probable causes remain unclear. We conducted a population-based longitudinal cohort study in Nakajima, Nanao City, Japan. Between 2016 and 2018, 2454 residents aged ≥60 participated, covering 92.9% of the local age demographics. This study used comprehensive approach by combining detailed dental examinations, dietary assessments, magnetic resonance imaging (MRI) analysis, and cognitive evaluations. Tooth loss, even in cognitively normal individuals, is associated with parahippocampal gyrus atrophy and increased WMH volume, both of which are characteristics of dementia. Tooth loss was associated with altered dietary patterns, notably a reduction in plant-based food intake and an increase in fatty, processed food intake. This study highlights a possible preventative pathway where oral health may play a significant role in preventing the early neuropathological shifts associated with dementia.

Functional and structural gradients reveal atypical hierarchical organization of Parkinson's disease

Parkinson's disease (PD) patients exhibit deficits in primary sensorimotor and higher-order executive functions. The gradient reflects the functional spectrum in sensorimotor-associated areas of the brain. We aimed to determine whether the gradient is disrupted in PD patients and how this disruption is associated with treatment outcome. Seventy-six patients (mean age, 59.2 ± 12.4 years [standard deviation], 44 women) and 34 controls participants (mean age, 58.1 ± 10.0 years [standard deviation], 19 women) were evaluated. We explored functional and structural gradients in PD patients and control participants. Patients were followed during 2 weeks of multidisciplinary intensive rehabilitation therapy (MIRT). The Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) was administered to patients before and after treatment. We investigated PD-related alterations in the principal functional and structural gradients. We further used a support vector machine (SVM) and correlation analysis to assess the classification ability and treatment outcomes related to PD gradient alterations, respectively. The gradients showed significant differences between patients and control participants, mainly in somatosensory and visual networks involved in primary function, and higher-level association networks (dorsal attentional network (DAN) and default mode network (DMN)) related to motor control and execution. On the basis of the combined functional and structural gradient features of these networks, the SVM achieved an accuracy of 91.2% in discriminating patients from control participants. Treatment reduced the gradient difference. The altered gradient exhibited a significant correlation with motor improvement and was mainly distributed across the visual network, DAN and DMN. This study revealed damage to gradients in the brain characterized by sensorimotor and executive control deficits in PD patients. The application of gradient features to neurological disorders could lead to the development of potential diagnostic and treatment markers for PD.

Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases

Neurodegenerative diseases (NDs) such as Alzheimer's Disease (AD) and Parkinson's Disease (PD) are devastating conditions that can develop without noticeable symptoms, causing irreversible damage to neurons before any signs become clinically evident. NDs are a major cause of disability and mortality worldwide. Currently, there are no cures or treatments to halt their progression. Therefore, the development of early detection methods is urgently needed to delay neuronal loss as soon as possible. Despite advancements in Medtech, the early diagnosis of NDs remains a challenge at the intersection of medical, IT, and regulatory fields. Thus, this review explores "digital biomarkers" (tools designed for remote neurocognitive data collection and AI analysis) as a potential solution. The review summarizes that recent studies combining AI with digital biomarkers suggest the possibility of identifying pre-symptomatic indicators of NDs. For instance, research utilizing convolutional neural networks for eye tracking has achieved significant diagnostic accuracies. ROC-AUC scores reached up to 0.88, indicating high model performance in differentiating between PD patients and healthy controls. Similarly, advancements in facial expression analysis through tools have demonstrated significant potential in detecting emotional changes in ND patients, with some models reaching an accuracy of 0.89 and a precision of 0.85. This review follows a structured approach to article selection, starting with a comprehensive database search and culminating in a rigorous quality assessment and meaning for NDs of the different methods. The process is visualized in 10 tables with 54 parameters describing different approaches and their consequences for understanding various mechanisms in ND changes. However, these methods also face challenges related to data accuracy and privacy concerns. To address these issues, this review proposes strategies that emphasize the need for rigorous validation and rapid integration into clinical practice. Such integration could transform ND diagnostics, making early detection tools more cost-effective and globally accessible. In conclusion, this review underscores the urgent need to incorporate validated digital health tools into mainstream medical practice. This integration could indicate a new era in the early diagnosis of neurodegenerative diseases, potentially altering the trajectory of these conditions for millions worldwide. Thus, by highlighting specific and statistically significant findings, this review demonstrates the current progress in this field and the potential impact of these advancements on the global management of NDs.

Liensinine and neferine exert neuroprotective effects via the autophagy pathway in transgenic Caenorhabditis elegans

BACKGROUND

Liensinine and neferine are the main bisbenzylisoquinoline alkaloids obtained from the seeds of Nelumbo nucifera, which commonly used as edible food and traditional medicine in Asia. It was reported that liensinine and neferine could inhibit the activities of acetylcholinesterase and cross the blood-brain barriers, suggesting their therapeutic potential for the management of Alzheimer's disease.

METHODS

Here, we employed SH-SY5Y human neuroblastoma cells stably transfected with the human Swedish amyloid precursor protein (APP) mutation APP695 (APP695swe SH-SY5Y) as an in vitro model and transgenic Caenorhabditis elegans as an in vivo model to investigate the neuroprotective effects and underlying mechanism of liensinine and neferine.

RESULTS

We found that liensinine and neferine could significantly improve the viability and reduce ROS levels in APP695swe SH-SY5Y cells, inhibit β-amyloid and tau-induced toxicity, and enhance stress resistance in nematodes. Moreover, liensinine and neferine had obviously neuroprotective effects by assaying chemotaxis, 5-hydroxytryptamine sensitivity and the integrity of injured neurons in nematodes. Preliminary mechanism studies revealed that liensinine and neferine could upregulate the expression of autophagy related genes (lgg-1, unc-51, pha-4, atg-9 and ced-9) and reduce the accumulation of β-amyloid induced autophagosomes, which suggested autophagy pathway played a key role in neuroprotective effects of these two alkaloids.

CONCLUSIONS

Altogether, our findings provided a certain working foundation for the use of liensinine and neferine to treat Alzheimer's disease based on neuroprotective effects.

Bibliometric review on biomarkers for Alzheimer's disease between 2000 and 2023

BACKGROUND

Alzheimer's disease (AD) is a common cause of dementia and frailty. Therefore, it is important to develop biomarkers that can diagnose these changes to improve the likelihood of monitoring and treating potential causes. Therefore, this study aimed to examine the relationship between biomarkers and AD, identify journal publications and collaborators, and analyze keywords and research trends using a bibliometric method.

METHODS

We systematically searched for papers published in the Web of Science Core Collection database on biomarkers and AD. The search strategy was as follows: (TS) = (Alzheimer's OR Alzheimer's OR Alzheimer OR "Alzheimer's disease" OR "Alzheimer disease") AND TS = (biomarker OR biomarkers). Only articles and reviews were included as document types, with English as the primary language. The CiteSpace software was used to analyze the retrieved data on countries/regions, institutions, authors, published journals, and keywords. Simultaneously, the co-occurrence of the keywords was constructed.

RESULTS

There were 2625 articles on biomarkers and AD research published by 51 institutions located in 41 countries in 75 journals; the number of articles has shown an increasing trend over the past 20 years. Keywords analysis showed that Alzheimer's disease, cerebrospinal fluid, mild cognitive impairment, amyloid beta, and tau were also highly influential.

CONCLUSION

This was the first study to provide an overview of the current status of development, hot spots of study, and future trends in biomarkers for AD. These findings will provide useful information for researchers to explore trends and gaps in the field of biomarkers and AD.

Bioinformatic analysis of the SPs and NFTs proteomes unravel putative biomarker candidates for Alzheimer's disease

Aging is the main risk factor for the appearance of age-related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks in AD brains. The core of these deposits are predominantly amyloid fibrils in SPs and hyperphosphorylated Tau protein in NFTs, but other molecular components can be found associated with these pathological lesions. Herein, an extensive literature review was carried out to obtain the SPs and NFTs proteomes, followed by a bioinformatic analysis and further putative biomarker validation. For SPs, 857 proteins were recovered, and, for NFTs, 627 proteins of which 375 occur in both groups and represent the common proteome. Gene Ontology (GO) enrichment analysis permitted the identification of biological processes and the molecular functions most associated with these lesions. Analysis of the SPs and NFTs common proteins unraveled pathways and molecular targets linking both histopathological events. Further, validation of a putative phosphotarget arising from the in silico analysis was performed in serum-derived extracellular vesicles from AD patients. This bioinformatic approach contributed to the identification of putative molecular targets, valuable for AD diagnostic or therapeutic intervention.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

Challenges and opportunities of diagnostic markers of Alzheimer's disease based on structural magnetic resonance imaging

OBJECTIVES

This article aimed to carry out a narrative literature review of early diagnostic markers of Alzheimer's disease (AD) based on both micro and macro levels of pathology, indicating the shortcomings of current biomarkers and proposing a novel biomarker of structural integrity that associates the hippocampus and adjacent ventricle together. This could help to reduce the influence of individual variety and improve the accuracy and validity of structural biomarker.

METHODS

This review was based on presenting comprehensive background of early diagnostic markers of AD. We have compiled those markers into micro level and macro level, and discussed the advantages and disadvantages of them. Eventually the ratio of gray matter volume to ventricle volume was put forward.

RESULTS

The costly methodologies and related high patient burden of "micro" biomarkers (cerebrospinal fluid biomarkers) hinder the implementation in routine clinical examination. In terms of "macro" biomarkers- hippocampal volume (HV), there is a large variation of it among population, which undermines its validity Considering the gray matter atrophies while the adjacent ventricular volume enlarges, we assume the hippocampal to ventricle ratio (HVR) is a more reliable marker than HV alone the emerging evidence showed hippocampal to ventricle ratio predicts memory functions better than HV alone in elderly sample.

CONCLUSIONS

The ratio between gray matter structures and adjacent ventricular volumes counts as a promising superior diagnostic marker of early neurodegeneration.

Translational potential of synaptic alterations in Alzheimer's disease patients and amyloid precursor protein knock-in mice

Synaptic dysfunction is an early event in Alzheimer's disease. Post-mortem studies suggest that alterations in synaptic proteins are associated with cognitive decline in Alzheimer's disease. We measured the concentration of three synaptic proteins, zinc transporter protein 3, dynamin1 and AMPA glutamate receptor 3 in cerebrospinal fluid of subjects with mild cognitive impairment (n = 18) and Alzheimer's disease (n = 18) and compared the levels to cognitively and neurologically healthy controls (n = 18) by using ELISA assay. In addition, we aimed to assess the translational potential of these synaptic proteins in two established amyloid precursor protein knock-in Alzheimer's disease mouse models by assessing the cerebrospinal fluid, hippocampal and cortical synaptic protein concentrations. Using ELISA, we measured in parallel these three proteins in cerebrospinal fluid and/or brain of 12- and 24-month-old App^NL-F and App^NL-G-F knock-in mice and App^Wt control mice. The regional distribution and expression of these proteins were explored upon aging of the App knock-in models by quantitative immunofluorescence microscopy. Notably, we found a significant increase in concentrations of zinc transporter protein 3 and AMPA glutamate receptor 3 in cerebrospinal fluid of both patient groups compared with cognitively healthy controls. Dynamin1 concentration was significantly higher in Alzheimer's disease patients. Remarkably, patients with mild cognitive impairment who converted to Alzheimer's disease (n = 7) within 2 years exhibited elevated baseline cerebrospinal fluid zinc transporter protein 3 concentrations compared with mild cognitive impairment patients who did not convert (n = 11). Interestingly, similar to the alterations in Alzheimer's disease subjects, cerebrospinal fluid AMPA glutamate receptor 3 concentration was significantly higher in App^NL-G-F knock-in mice when compared with wild-type controls. Furthermore, we have detected age and brain regional specific changes of the three synaptic proteins in the hippocampus and prefrontal cortex of both App^NL-F and App^NL-G-F knock-in mice. Notably, all the three cerebrospinal fluid synaptic protein concentrations correlated negatively with concentrations in hippocampal lysates. The elevated zinc transporter protein 3 concentrations in the cerebrospinal fluid of converter versus non-converter mild cognitive impairment patients suggests a prospective role of zinc transporter 3 in differentiating dementia patients of the biological continuum of Alzheimer's disease. The increased cerebrospinal fluid concentrations of synaptic proteins in both patient groups, potentially reflecting synaptic alterations in the brain, were similarly observed in the amyloid precursor protein knock-in mouse models highlighting the translational potential of these proteins as markers for synaptic alterations. These synaptic markers could potentially help reduce the current disparities between human and animal model-based studies aiding the translation of preclinical discoveries of pathophysiological changes into clinical research.

CNN for a Regression Machine Learning Algorithm for Predicting Cognitive Impairment Using qEEG

Purpose

Electroencephalogram (EEG) signals give detailed information on the electrical brain activities occurring in the cerebral cortex. They are used to study brain-related disorders such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). Brain signals obtained using an EEG machine can be a neurophysiological biomarker for early diagnosis of dementia through quantitative EEG (qEEG) analysis. This paper proposes a machine learning methodology to detect MCI and AD from qEEG time-frequency (TF) images of the subjects in an eyes-closed resting state (ECR).

Participants and Methods

The dataset consisted of 16,910 TF images from 890 subjects: 269 healthy controls (HC), 356 MCI, and 265 AD. First, EEG signals were transformed into TF images using a Fast Fourier Transform (FFT) containing different event-rated changes of frequency sub-bands preprocessed from the EEGlab toolbox in the MATLAB R2021a environment software. The preprocessed TF images were applied in a convolutional neural network (CNN) with adjusted parameters. For classification, the computed image features were concatenated with age data and went through the feed-forward neural network (FNN).

Results

The trained models', HC vs MCI, HC vs AD, and HC vs CASE (MCI + AD), performance metrics were evaluated based on the test dataset of the subjects. The accuracy, sensitivity, and specificity were evaluated: HC vs MCI was 83%, 93%, and 73%, HC vs AD was 81%, 80%, and 83%, and HC vs CASE (MCI + AD) was 88%, 80%, and 90%, respectively.

Conclusion

The proposed models trained with TF images and age can be used to assist clinicians as a biomarker in detecting cognitively impaired subjects at an early stage in clinical sectors.

Dexmedetomidine Increases MMP-12 and MBP Concentrations after Coronary Artery Bypass Graft Surgery with Extracorporeal Circulation Anaesthesia without Impacting Cognitive Function: A Randomised Control Trial

Postoperative neurological deficits remain a concern for patients undergoing cardiac surgeries. Even minor injuries can lead to neurocognitive decline (i.e., postoperative cognitive dysfunction). Dexmedetomidine may be beneficial given its reported neuroprotective effect. We aimed to investigate the effects of dexmedetomidine on brain injury during cardiac surgery anaesthesia. This prospective observational study analysed data for 46 patients who underwent coronary artery bypass graft surgery with extracorporeal circulation between August 2018 and March 2019. The patients were divided into two groups: control (CON) with typical anaesthesia and dexmedetomidine (DEX) with dexmedetomidine infusion. Concentrations of the biomarkers matrix metalloproteinase-12 (MMP-12) and myelin basic protein (MBP) were measured preoperatively and at 24 and 72 h postoperatively. Cognitive evaluations were performed preoperatively, at discharge, and 3 months after discharge using Addenbrooke's Cognitive Examination version III (ACE-III). The primary endpoint was the ACE-III score at discharge. Increased MMP-12 and MBP concentrations were observed in the DEX group 24 and 72 h postoperatively. No significant differences in ACE-III scores were observed between the groups at discharge; however, the values were increased when compared with initial values after 3 months (p = 0.000). The current results indicate that the administration of dexmedetomidine as an adjuvant to anaesthesia can increase MMP-12 and MBP levels without effects on neurocognitive outcomes at discharge and 3 months postoperatively.

Associations between cerebrospinal fluid markers and cognition in ageing and dementia: A systematic review

A biomarker associated with cognition in neurodegenerative dementias would aid in the early detection of disease progression, complement clinical staging and act as a surrogate endpoint in clinical trials. The current systematic review evaluates the association between cerebrospinal fluid protein markers of synapse loss and neuronal injury and cognition. We performed a systematic search which revealed 67 studies reporting an association between cerebrospinal fluid markers of interest and neuropsychological performance. Despite the substantial heterogeneity between studies, we found some evidence for an association between neurofilament-light and worse cognition in Alzheimer's diseases, frontotemporal dementia and typical cognitive ageing. Moreover, there was an association between cerebrospinal fluid neurogranin and cognition in those with an Alzheimer's-like cerebrospinal fluid biomarker profile. Some evidence was found for cerebrospinal fluid neuronal pentraxin-2 as a correlate of cognition across dementia syndromes. Due to the substantial heterogeneity of the field, no firm conclusions can be drawn from this review. Future research should focus on improving standardization and reporting as well as establishing the importance of novel markers such as neuronal pentraxin-2 and whether such markers can predict longitudinal cognitive decline.

The significance of glycolysis index and its correlations with immune infiltrates in Alzheimer’s disease

Alzheimer’s disease (AD) is a common neurodegenerative disorder without an effective treatment, and results in an increasingly serious health problem. However, its pathogenesis is complex and poorly understood. Nonetheless, the exact role of dysfunctional glucose metabolism in AD pathogenesis remains unclear. We screened 28 core glycolysis-related genes and introduced a novel metric, the glycolysis index, to estimate the activation of glycolysis. The glycolysis index was significantly lower in the AD group in four different brain regions (frontal cortex, FC; temporal cortex, TC; hippocampus, HP; and entorhinal cortex, EC) than that in the control group. Combined with differential expression and over-representation analyses, we determined the clinical and pathological relevance of glycolysis in AD. Subsequently, we investigated the role of glycolysis in the AD brain microenvironment. We developed a glycolysis-brain cell marker connection network, which revealed a close relationship between glycolysis and seven brain cell types, most of which presented abundant variants in AD. Using immunohistochemistry, we detected greater infiltrated microglia and higher expression of glycolysis-related microglia markers in the APP/PS1 AD model than that in the control group, consistent with our bioinformatic analysis results. Furthermore, the excellent predictive value of the glycolysis index has been verified in different populations. Overall, our present findings revealed the clinical and biological significance of glycolysis and the brain microenvironment in AD.

Lead-exposure associated miRNAs in humans and Alzheimer's disease as potential biomarkers of the disease and disease processes

Alzheimer's disease (AD) is a neurodegenerative disease that eventually affects memory and behavior. The identification of biomarkers based on risk factors for AD provides insight into the disease since the exact cause of AD remains unknown. Several studies have proposed microRNAs (miRNAs) in blood as potential biomarkers for AD. Exposure to heavy metals is a potential risk factor for onset and development of AD. Blood cells of subjects that are exposed to lead detected in the circulatory system, potentially reflect molecular responses to this exposure that are similar to the response of neurons. In this study we analyzed blood cell-derived miRNAs derived from a general population as proxies of potentially AD-related mechanisms triggered by lead exposure. Subsequently, we analyzed these mechanisms in the brain tissue of AD subjects and controls. A total of four miRNAs were identified as lead exposure-associated with hsa-miR-3651, hsa-miR-150-5p and hsa-miR-664b-3p being negatively and hsa-miR-627 positively associated. In human brain derived from AD and AD control subjects all four miRNAs were detected. Moreover, two miRNAs (miR-3651, miR-664b-3p) showed significant differential expression in AD brains versus controls, in accordance with the change direction of lead exposure. The miRNAs' gene targets were validated for expression in the human brain and were found enriched in AD-relevant pathways such as axon guidance. Moreover, we identified several AD relevant transcription factors such as CREB1 associated with the identified miRNAs. These findings suggest that the identified miRNAs are involved in the development of AD and might be useful in the development of new, less invasive biomarkers for monitoring of novel therapies or of processes involved in AD development.

Oroxylin A: A Promising Flavonoid for Prevention and Treatment of Chronic Diseases

There have been magnificent advancements in the understanding of molecular mechanisms of chronic diseases over the past several years, but these diseases continue to be a considerable cause of death worldwide. Most of the approved medications available for the prevention and treatment of these diseases target only a single gene/protein/pathway and are known to cause severe side effects and are less effective than they are anticipated. Consequently, the development of finer therapeutics that outshine the existing ones is far-reaching. Natural compounds have enormous applications in curbing several disastrous and fatal diseases. Oroxylin A (OA) is a flavonoid obtained from the plants Oroxylum indicum, Scutellaria baicalensis, and S. lateriflora, which have distinctive pharmacological properties. OA modulates the important signaling pathways, including NF-κB, MAPK, ERK1/2, Wnt/β-catenin, PTEN/PI3K/Akt, and signaling molecules, such as TNF-α, TGF-β, MMPs, VEGF, interleukins, Bcl-2, caspases, HIF-1α, EMT proteins, Nrf-2, etc., which play a pivotal role in the molecular mechanism of chronic diseases. Overwhelming pieces of evidence expound on the anti-inflammatory, anti-bacterial, anti-viral, and anti-cancer potentials of this flavonoid, which makes it an engrossing compound for research. Numerous preclinical and clinical studies also displayed the promising potential of OA against cancer, cardiovascular diseases, inflammation, neurological disorders, rheumatoid arthritis, osteoarthritis, etc. Therefore, the current review focuses on delineating the role of OA in combating different chronic diseases and highlighting the intrinsic molecular mechanisms of its action.

Alzheimer's disease amyloid-β pathology in the lens of the eye

Neuropathological hallmarks of Alzheimer's disease (AD) include pathogenic accumulation of amyloid-β (Aβ) peptides and age-dependent formation of amyloid plaques in the brain. AD-associated Aβ neuropathology begins decades before onset of cognitive symptoms and slowly progresses over the course of the disease. We previously reported discovery of Aβ deposition, β-amyloidopathy, and co-localizing supranuclear cataracts (SNC) in lenses from people with AD, but not other neurodegenerative disorders or normal aging. We confirmed AD-associated Aβ molecular pathology in the lens by immunohistopathology, amyloid histochemistry, immunoblot analysis, epitope mapping, immunogold electron microscopy, quantitative immunoassays, and tryptic digest mass spectrometry peptide sequencing. Ultrastructural analysis revealed that AD-associated Aβ deposits in AD lenses localize as electron-dense microaggregates in the cytoplasm of supranuclear (deep cortex) fiber cells. These Aβ microaggregates also contain αB-crystallin and scatter light, thus linking Aβ pathology and SNC phenotype expression in the lenses of people with AD. Subsequent research identified Aβ lens pathology as the molecular origin of the distinctive cataracts associated with Down syndrome (DS, trisomy 21), a chromosomal disorder invariantly associated with early-onset Aβ accumulation and Aβ amyloidopathy in the brain. Investigation of 1249 participants in the Framingham Eye Study found that AD-associated quantitative traits in brain and lens are co-heritable. Moreover, AD-associated lens traits preceded MRI brain traits and cognitive deficits by a decade or more and predicted future AD. A genome-wide association study of bivariate outcomes in the same subjects identified a new AD risk factor locus in the CTNND2 gene encoding δ-catenin, a protein that modulates Aβ production in brain and lens. Here we report identification of AD-related human Aβ (hAβ) lens pathology and age-dependent SNC phenotype expression in the Tg2576 transgenic mouse model of AD. Tg2576 mice express Swedish mutant human amyloid precursor protein (APP-Swe), accumulate hAβ peptides and amyloid pathology in the brain, and exhibit cognitive deficits that slowly progress with increasing age. We found that Tg2576 trangenic (Tg⁺) mice, but not non-transgenic (Tg^-) control mice, also express human APP, accumulate hAβ peptides, and develop hAβ molecular and ultrastructural pathologies in the lens. Tg2576 Tg⁺ mice exhibit age-dependent Aβ supranuclear lens opacification that recapitulates lens pathology and SNC phenotype expression in human AD. In addition, we detected hAβ in conditioned medium from lens explant cultures prepared from Tg⁺ mice, but not Tg^- control mice, a finding consistent with constitutive hAβ generation in the lens. In vitro studies showed that hAβ promoted mouse lens protein aggregation detected by quasi-elastic light scattering (QLS) spectroscopy. These results support mechanistic (genotype-phenotype) linkage between Aβ pathology and AD-related phenotypes in lens and brain. Collectively, our findings identify Aβ pathology as the shared molecular etiology of two age-dependent AD-related cataracts associated with two human diseases (AD, DS) and homologous murine cataracts in the Tg2576 transgenic mouse model of AD. These results represent the first evidence of AD-related Aβ pathology outside the brain and point to lens Aβ as an optically-accessible AD biomarker for early detection and longitudinal monitoring of this devastating neurodegenerative disease.

Rational Design of Quinoxalinone-Based Red-Emitting Probes for High-Affinity and Long-Term Visualizing Amyloid-β In Vivo

Alzheimer's disease (AD) is a progressive neurodegenerative disease with insidious onset, and the deposition of amyloid-β (Aβ) is believed to be one of the main cause. Fluorescence imaging is a promising technique for this task, but the Aβ gold standard probe ThT developed based on this still has shortcomings. The development of a new fluorescent probe to detect Aβ plaques is thought to be essential. Herein, a series of red to near-infrared emitting fluorescent probes QNO-ADs with newly quinoxalinone skeleton are designed to detect Aβ plaques. They all demonstrate excellent optical properties and high binding affinity (∼K_d = 20 nM) to Aβ aggregates. As the most outstanding candidate, QNO-AD-3 shows significant signal-to-noise (S/N) ratio at the level of in vitro binding studies, and the brilliant fluorescence staining results in favor of grasping the approximate distribution of Aβ plaques in the brain slice. In vivo Aβ plaques imaging suggests that QNO-AD-3 can cross the BBB and have a long retention time in the brain with low biological toxicity. In addition, the results of docking theoretical calculation also provide some references for the design of Aβ probe. Overall, given the high affinity of QNO-AD-3 and the ability to monitor Aβ plaques for a long time that is not common now, we believe QNO-AD-3 will be an effective tool for an Aβ-related matrix and AD disease research in the future.

Diagnostic Accuracy of the Five-Word Test for Mild Cognitive Impairment Due to Alzheimer's Disease

New diagnostic methods have been developed for the early diagnosis of Alzheimer’s disease (AD) with the primary purpose of intercepting the transition-phase (mild cognitive impairment, MCI) between normal aging and dementia. We aimed to explore whether the five-word test (FWT) and the mini-mental state examination (MMSE) are predictive for the early diagnosis of MCI due to AD (AD-MCI). We computed ROC analyses to evaluate the sensitivity and specificity of MMSE and FWT in predicting abnormal CSF (t-Tau, p-Tau181, Aβ1−42) and amyloid-PET biomarkers. AD-MCI patients showed lower MMSE and FWT scores (all p < 0.001) than non-AD-MCI. The best predictor of amyloid plaques’ presence at amyloid-PET imaging was the encoding sub-score of the FWT (AUC = 0.84). Both FWT and MMSE had low/moderate accuracy for the detection of pathological CSF Aβ42, t-Tau and p-Tau181 values, with higher accuracy for the t-Tau/Aβ1−42 ratio. In conclusion, the FWT, as a single-domain cognitive screening test, seems to be prompt and moderately accurate tool for the identification of an underlying AD neuropathological process in patients with MCI, supporting the importance of associating biomarkers evaluation in the work-up of patients with dementing neurodegenerative disorders.

Salivary biomarkers of neurodegenerative and demyelinating diseases and biosensors for their detection

Salivary analysis is gaining increasing interest as a novel and promising field of research for the diagnosis of neurodegenerative and demyelinating diseases related to aging. The collection of saliva offers several advantages, being noninvasive, stress-free, and repeatable. Moreover, the detection of biomarkers directly in saliva could allow an early diagnosis of the disease, leading to timely treatments. The aim of this manuscript is to highlight the most relevant researchers' findings relatively to salivary biomarkers of neurodegenerative and demyelinating diseases, and to describe innovative and advanced biosensing strategies for the detection of salivary biomarkers. This review is focused on five relevant aging-related neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, Huntington's disease, Multiple Sclerosis) and the salivary biomarkers most commonly associated with them. Advanced biosensors enabling molecular diagnostics for the detection of salivary biomarkers are presented, in order to stimulate future research in this direction and pave the way for their clinical application.

Oral and Laryngeal Diadochokinesis Across the Life Span: A Scoping Review of Methods, Reference Data, and Clinical Applications

PURPOSE

The aim of this study was to conduct a scoping review of research on oral and laryngeal diadochokinesis (DDK) in children and adults, either typically developing/developed or with a clinical diagnosis.

METHOD

Searches were conducted with PubMed/MEDLINE, Google Scholar, CINAHL, and legacy sources in retrieved articles. Search terms included the following: DDK, alternating motion rate, maximum repetition rate, sequential motion rate, and syllable repetition rate.

RESULTS

Three hundred sixty articles were retrieved and included in the review. Data source tables for children and adults list the number and ages of study participants, DDK task, and language(s) spoken. Cross-sectional data for typically developing children and typically developed adults are compiled for the monosyllables /pʌ/, /tʌ/, and /kʌ/; the trisyllable /pʌtʌkʌ/; and laryngeal DDK. In addition, DDK results are summarized for 26 disorders or conditions.

DISCUSSION

A growing number of multidisciplinary reports on DDK affirm its role in clinical practice and research across the world. Atypical DDK is not a well-defined singular entity but rather a label for a collection of disturbances associated with diverse etiologies, including motoric, structural, sensory, and cognitive. The clinical value of DDK can be optimized by consideration of task parameters, analysis method, and population of interest.

Reduced parietal activation in participants with mild cognitive impairments during visual-spatial processing measured with functional near-infrared spectroscopy

Functional Near Infrared Spectroscopy (fNIRS) may be a suitable, simple, and cost-effective brain imaging technique for detecting divergent neuronal patterns at an early stage of neurodegeneration. In course of Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD), a deficit in visual-spatial processing, located in the parietal cortex, is a reliable risk factor. Earlier, we established the application of the clock-hand-angle-discrimination task (ADT) during fNIRS to identify neuronal correlates of the visual-spatial processing in a healthy elderly sample. In this analysis, we aimed to measure and find out differences in the hemodynamic response in MCI participants compared to matched healthy controls. As expected, MCI participants showed more errors over all conditions of pointer length and a higher reaction time in the long and middle pointer length condition. Moreover, results revealed a significant reduction of cortical activation in MCI patients. There was a generally increased activity in both the right as compared to the left hemisphere and the superior parietal brain region as compared to the inferior parietal brain region in both groups. In summary, fNIRS can be implemented in the measurement of visual-spatial processing in MCI patients and healthy elderly based on ADT. MCI participants had difficulties to cope with the ADT. Since neuronal hypoactivity occurs with concomitant behavioral deficits, an additional analysis was performed on a subgroup of MCI patients who performed as well as the control group in behavior. This subgroup analysis also showed a hypoactivation of the parietal cortex, without evidence of a compensatory activation. Therefore, we assume that MCI patients are characterized by a deficit in the parietal cortex. Overall, these findings confirm our hypothesis that hemodynamic deficits in visual-spatial processing, localized in the parietal cortex, are reliable and early diagnostic markers for cognitive decline in risk groups for the development of AD.

Prediction and Modeling of Neuropsychological Scores in Alzheimer's Disease Using Multimodal Neuroimaging Data and Artificial Neural Networks

Background: In recent years, predicting and modeling the progression of Alzheimer's disease (AD) based on neuropsychological tests has become increasingly appealing in AD research. Objective: In this study, we aimed to predict the neuropsychological scores and investigate the non-linear progression trend of the cognitive declines based on multimodal neuroimaging data. Methods: We utilized unimodal/bimodal neuroimaging measures and a non-linear regression method (based on artificial neural networks) to predict the neuropsychological scores in a large number of subjects (n = 1143), including healthy controls (HC) and patients with mild cognitive impairment non-converter (MCI-NC), mild cognitive impairment converter (MCI-C), and AD. We predicted two neuropsychological scores, i.e., the clinical dementia rating sum of boxes (CDRSB) and Alzheimer's disease assessment scale cognitive 13 (ADAS13), based on structural magnetic resonance imaging (sMRI) and positron emission tomography (PET) biomarkers. Results: Our results revealed that volumes of the entorhinal cortex and hippocampus and the average fluorodeoxyglucose (FDG)-PET of the angular gyrus, temporal gyrus, and posterior cingulate outperform other neuroimaging features in predicting ADAS13 and CDRSB scores. Compared to a unimodal approach, our results showed that a bimodal approach of integrating the top two neuroimaging features (i.e., the entorhinal volume and the average FDG of the angular gyrus, temporal gyrus, and posterior cingulate) increased the prediction performance of ADAS13 and CDRSB scores in the converting and stable stages of MCI and AD. Finally, a non-linear AD progression trend was modeled to describe the cognitive decline based on neuroimaging biomarkers in different stages of AD. Conclusion: Findings in this study show an association between neuropsychological scores and sMRI and FDG-PET biomarkers from normal aging to severe AD.

Deficits in color detection in patients with Alzheimer disease

Deficits in color vision and related retinal changes hold promise as early screening biomarkers in patients with Alzheimer’s disease. This study aimed to determine a cut-off score that can screen for Alzheimer’s dementia using a novel color vision threshold test named the red, green, and blue (RGB) modified color vision plate test (RGB-vision plate). We developed the RGB-vision plate consisting of 30 plates in which the red and green hues of Ishihara Plate No.22 were sequentially adjusted. A total of 108 older people participated in the mini-mental state examination (MMSE), Ishihara plate, and RGB-vision plate. For the analyses, the participants were divided into two groups: Alzheimer’s dementia (n = 42) and healthy controls (n = 38). K-means cluster analysis and ROC curve analysis were performed to identify the most appropriate cut-off score. As a result, the cut-off screening score for Alzheimer’s dementia on the RGB-vision plate was set at 25, with an area under the curve of 0.773 (p<0.001). Moreover, there was a negative correlation between the RGB-vision plate thresholds and MMSE scores (r = -0.36, p = 0.02). In conclusion, patients with Alzheimer’s dementia had a deficit in color vision. The RGB-vision plate is a potential early biomarker that may adequately detect Alzheimer’s dementia.

Recent Advancements in Nanodiamond Mediated Brain Targeted Drug Delivery and Bioimaging of Brain Ailments: A Holistic Review

BACKGROUND

The brain is a vital and composite organ. By nature, the innate make-up of the brain is such that in anatomical parlance, it is highly protected by the "Blood-Brain Barrier", which is a nexus of capillary endothelial cells, basement membrane, neuroglial membrane and glialpodocytes. The same barrier, which protects and isolates the interstitial fluid of the brain from capillary circulation, also restricts the therapeutic intervention. Many standing pharmaceutical formulations are ineffective in the treatment of inimical brain ailments because of the inability of the API to surpass and subsist inside the Blood Brain Barrier.

OBJECTIVE

This is an integrated review that emphasizes on the recent advancements in brain-targeted drug delivery utilizing nanodiamonds (NDs) as a carrier of therapeutic agents. NDs are a novel nanoparticulate drug delivery system, having carbon moieties as their building blocks and their surface tenability is remarkable. These neoteric carbon-based carriers have exceptional, mechanical, electrical, chemical, optical, and biological properties, which can be further rationally modified and augmented.

CONCLUSION

NDs could be the next"revolution "in the field of nanoscience for the treatment of neurodegenerative disorders, brain tumors, and other pernicious brain ailments. What sets them apart from other nanocarriers is their versatile properties like diverse size range and surface modification potential, which makes them efficient enough to move across certain biological barriers and offer a plethora of brain targeting and bioimaging abilities. Lay Summary: The blood-brain barrier (BBB) poses a major hurdle in the way of treating many serious brain ailments. A range of nanoparticle based drug delivering systems have been formulated, including solid lipid nanoparticles, liposomes, dendrimers, nanogels, polymeric NPs, metallic NPs (gold, platinum, andironoxide) and diamondoids (carbonnanotubes). Despite this development, only a few of these formulations have shown the ability to cross the BBB. Nanodiamonds, because of their small size, shape, and surface characteristics, have a potential in moving beyond the diverse and intricate BBB, and offer a plethora of brain targeting capabilities.

Emerging Application of Magnetic Nanoparticles for Diagnosis and Treatment of Cancer

Cancer is a disease that has resulted in millions of deaths worldwide. The current conventional therapies utilized for the treatment of cancer have detrimental side effects. This led scientific researchers to explore new therapeutic avenues with an improved benefit to risk profile. Researchers have found nanoparticles, particles between the 1 and 100 nm range, to be encouraging tools in the area of cancer. Magnetic nanoparticles are one of many available nanoparticles at present. Magnetic nanoparticles have increasingly been receiving a considerable amount of attention in recent years owing to their unique magnetic properties, among many others. Magnetic nanoparticles can be controlled by an external magnetic field, signifying their ability to be site specific. The most popular approaches for the synthesis of magnetic nanoparticles are co-precipitation, thermal decomposition, hydrothermal, and polyol synthesis. The functionalization of magnetic nanoparticles is essential as it significantly increases their biocompatibility. The most utilized functionalization agents are comprised of polymers. The synthesis and functionalization of magnetic nanoparticles will be further explored in this review. The biomedical applications of magnetic nanoparticles investigated in this review are drug delivery, magnetic hyperthermia, and diagnosis. The diagnosis aspect focuses on the utilization of magnetic nanoparticles as contrast agents in magnetic resonance imaging. Clinical trials and toxicology studies relating to the application of magnetic nanoparticles for the diagnosis and treatment of cancer will also be discussed in this review.

Nanoparticle-based colorimetric sensors to detect neurodegenerative disease biomarkers

Neurodegenerative disorders (NDDs) are progressive, incurable health conditions that primarily affect brain cells, and result in loss of brain mass and impaired function. Current sensing technologies for NDD detection are limited by high cost, long sample preparation, and/or require skilled personnel. To overcome these limitations, optical sensors, specifically colorimetric sensors, have garnered increasing attention towards the development of a cost-effective, simple, and rapid alternative approach. In this review, we evaluate colorimetric sensing strategies of NDD biomarkers (e.g. proteins, neurotransmitters, bio-thiols, and sulfide), address the limitations and challenges of optical sensor technologies, and provide our outlook on the future of this field.

Analysis of Shared Genetic Regulatory Networks for Alzheimer's Disease and Epilepsy

Alzheimer's disease (AD) and epilepsy are neurological disorders that affect a large cohort of people worldwide. Although both of the two diseases could be influenced by genetic factors, the shared genetic mechanism underlying the pathogenesis of them is still unclear. In this study, we aimed to identify the shared genetic networks and corresponding hub genes for AD and epilepsy. Firstly, the gene coexpression modules (GCMs) were constructed by weighted gene coexpression network analysis (WGCNA), and 16 GCMs were identified. Through further integration of GCMs, genome-wide association studies (GWASs), and expression quantitative trait loci (eQTLs), 4 shared GCMs of AD and epilepsy were identified. Functional enrichment analysis was performed to analyze the shared biological processes of these GCMs and explore the functional overlaps between these two diseases. The results showed that the genes in shared GCMs were significantly enriched in nervous system-related pathways, such as Alzheimer's disease and neuroactive ligand-receptor interaction pathways. Furthermore, the hub genes of AD- and epilepsy-associated GCMs were captured by weighted key driver analysis (wKDA), including TRPC1, C2ORF40, NR3C1, KIAA0368, MMT00043109, STEAP1, MSX1, KL, and CLIC6. The shared GCMs and hub genes might provide novel therapeutic targets for AD and epilepsy.

Altered Homotopic Functional Connectivity Within White Matter in the Early Stages of Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with memory loss and cognitive impairment. The white matter (WM) BOLD signal has recently been shown to provide an important role in understanding the intrinsic cerebral activity. Although the altered homotopic functional connectivity within gray matter (GM-HFC) has been examined in AD, the abnormal HFC to WM remains unknown. The present study sought to identify changes in the WM-HFC and anatomic characteristics by combining functional magnetic resonance imaging with diffusion tensor imaging (DTI). Resting-state and DTI magnetic resonance images were collected from the OASIS-3 dataset and consisted of 53 mild cognitive impairment (MCI) patients, 90 very MCI (VMCI), and 100 normal cognitive (NC) subjects. Voxel-mirrored HFC was adopted to examine whether WM-HFC was disrupted in VMCI and MCI participants. Moreover, the DTI technique was used to investigate whether specific alterations of WM-HFC were associated with anatomic characteristics. Support vector machine analyses were used to identify the MCI and VMCI participants using the abnormal WM-HFC as the features. Compared with NC, MCI, and VMCI participants showed significantly decreased GM-HFC in the middle occipital gyrus and inferior parietal gyrus and decreased WM-HFC in the bilateral middle occipital and parietal lobe-WM. In addition, specific WM-functional network alteration for the bilateral sub-lobar-WM was found in MCI subjects. MCI subjects showed abnormal anatomic characteristics for bilateral sub-lobar and parietal lobe-WM. Results of GM-HFC mainly showed common neuroimaging features for VMCI and MCI subjects, whereas analysis of WM-HFC showed specific clinical neuromarkers and effectively compensated for the lack of GM-HFC to distinguish NC, VMCI, and MCI subjects.

Functional Neurophysiological Biomarkers of Early-Stage Alzheimer's Disease: A Perspective of Network Hyperexcitability in Disease Progression

Network hyperexcitability (NH) has recently been suggested as a potential neurophysiological indicator of Alzheimer’s disease (AD), as new, more accurate biomarkers of AD are sought. NH has generated interest as a potential indicator of certain stages in the disease trajectory and even as a disease mechanism by which network dysfunction could be modulated. NH has been demonstrated in several animal models of AD pathology and multiple lines of evidence point to the existence of NH in patients with AD, strongly supporting the physiological and clinical relevance of this readout. Several hypotheses have been put forward to explain the prevalence of NH in animal models through neurophysiological, biochemical, and imaging techniques. However, some of these hypotheses have been built on animal models with limitations and caveats that may have derived NH through other mechanisms or mechanisms without translational validity to sporadic AD patients, potentially leading to an erroneous conclusion of the underlying cause of NH occurring in patients with AD. In this review, we discuss the substantiation for NH in animal models of AD pathology and in human patients, as well as some of the hypotheses considering recently developed animal models that challenge existing hypotheses and mechanisms of NH. In addition, we provide a preclinical perspective on how the development of animal models incorporating AD-specific NH could provide physiologically relevant translational experimental data that may potentially aid the discovery and development of novel therapies for AD.

Genome-wide sequencing as a first-tier screening test for short tandem repeat expansions

Background

Screening for short tandem repeat (STR) expansions in next-generation sequencing data can enable diagnosis, optimal clinical management/treatment, and accurate genetic counseling of patients with repeat expansion disorders. We aimed to develop an efficient computational workflow for reliable detection of STR expansions in next-generation sequencing data and demonstrate its clinical utility.

Methods

We characterized the performance of eight STR analysis methods (lobSTR, HipSTR, RepeatSeq, ExpansionHunter, TREDPARSE, GangSTR, STRetch, and exSTRa) on next-generation sequencing datasets of samples with known disease-causing full-mutation STR expansions and genomes simulated to harbor repeat expansions at selected loci and optimized their sensitivity. We then used a machine learning decision tree classifier to identify an optimal combination of methods for full-mutation detection. In Burrows-Wheeler Aligner (BWA)-aligned genomes, the ensemble approach of using ExpansionHunter, STRetch, and exSTRa performed the best (precision = 82%, recall = 100%, F1-score = 90%). We applied this pipeline to screen 301 families of children with suspected genetic disorders.

Results

We identified 10 individuals with full-mutations in the AR, ATXN1, ATXN8, DMPK, FXN, or HTT disease STR locus in the analyzed families. Additional candidates identified in our analysis include two probands with borderline ATXN2 expansions between the established repeat size range for reduced-penetrance and full-penetrance full-mutation and seven individuals with FMR1 CGG repeats in the intermediate/premutation repeat size range. In 67 probands with a prior negative clinical PCR test for the FMR1, FXN, or DMPK disease STR locus, or the spinocerebellar ataxia disease STR panel, our pipeline did not falsely identify aberrant expansion. We performed clinical PCR tests on seven (out of 10) full-mutation samples identified by our pipeline and confirmed the expansion status in all, showing absolute concordance between our bioinformatics and molecular findings.

Conclusions

We have successfully demonstrated the application of a well-optimized bioinformatics pipeline that promotes the utility of genome-wide sequencing as a first-tier screening test to detect expansions of known disease STRs. Interrogating clinical next-generation sequencing data for pathogenic STR expansions using our ensemble pipeline can improve diagnostic yield and enhance clinical outcomes for patients with repeat expansion disorders.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00932-9.

Man's best friend in life and death: scientific perspectives and challenges of dog brain banking

Biobanking refers to the systematic collection, storage, and distribution of pre- or post-mortem biological samples derived from volunteer donors. The demand for high-quality human specimens is clearly demonstrated by the number of newly emerging biobanking facilities and large international collaborative networks. Several animal species are relevant today in medical research; therefore, similar initiatives in comparative physiology could be fruitful. Dogs, in particular, are gaining increasing attention in translational research on complex phenomena, like aging, cancer, and neurodegenerative diseases. Therefore, biobanks gathering and storing dog biological materials together with related data could play a vital role in translational and veterinary research projects. To achieve these aims, a canine biobank should meet the same standards in sample quality and data management as human biobanks and should rely on well-designed collaborative networks between different professionals and dog owners. While efforts to create dog biobanks could face similar financial and technical challenges as their human counterparts, they can widen the spectrum of successful collaborative initiatives towards a better picture of dogs’ physiology, disease, evolution, and translational potential. In this review, we provide an overview about the current state of dog biobanking and introduce the “Canine Brain and Tissue Bank” (CBTB)—a new, large-scale collaborative endeavor in the field.

Aberrant expression of miR-148a-3p in Alzheimer's disease and its protective role against amyloid-β induced neurotoxicity

OBJECTIVE

The current study investigated the expression change and clinical value of miR-148a-3p in AD patients, and further examined the role of miR-148a-3p in Aβ-induced neurotoxicity in SH-SY5Y cells.

MATERIAL AND METHODS

qRT-PCR was used for the measurement of miR-148a-3p expression levels. ROC curve was established to calculate the diagnostic value of serum miR-148a-3p for AD. CCK-8 and flow cytometry assay was applied for the detection of cell viability and apoptosis. Additionally, the luciferase reporter assay was performed to confirm the target relationship between ROCK1 and miR-148a-3p.

RESULTS

Serum miR-148a-3p was downregulated in AD patients compared with that in healthy controls, and was positively associated with the MMSE score in AD patients. Serum miR-148a-3p had the potential to distinguish AD patients from healthy controls, and the diagnostic sensitivity and specificity were respectively 85.5 % and 87.0 % at a cutoff value of 0.827. MiR-148a-3p attenuated Aβ25-35 induced neurotoxicity in SH-SY5Y cells, and ROCK1 was the target gene.

CONCLUSION

Serum miR-148a-3p is correlated with MMSE score in AD patients, and it might be helpful for the AD diagnosis. Overexpression of miR-148a-3p attenuated Aβ induced neurotoxicity in AD by targeting ROCK1.

In Vivo Brain Imaging of Amyloid-β Aggregates in Alzheimer's Disease with a Near-Infrared Fluorescent Probe

Abnormal accumulation of amyloid-β (Aβ) has been determined to be a critical factor for the progression of Alzheimer's disease (AD), which has motivated the development of new chemical approaches for early sensing and imaging of these Aβ aggregates. Herein, we report a new near-infrared (NIR) fluorescent probe for the selective monitoring of Aβ aggregates in vivo. This novel fluorophore, named CAQ, was based on the curcumin scaffold and was designed by introducing an intramolecular rotation donor and a quinoline functional group. CAQ was an environment-sensitive fluorescent probe that can be used as a reliable chemical tool for NIR imaging of amyloid plaques in a live Caenorhabditis elegans model of AD and in 5× FAD transgenic mice of early amyloid deposition. Our observations indicate that CAQ is promising for providing comprehensive information on neurodegenerative research, thereby promoting a deeper understanding of Alzheimer's pathological processes.

Biomarkers and the Role of α-Synuclein in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the presence of α-synuclein (α-Syn)-rich Lewy bodies (LBs) and the preferential loss of dopaminergic (DA) neurons in the substantia nigra (SN) pars compacta (SNpc). However, the widespread involvement of other central nervous systems (CNS) structures and peripheral tissues is now widely documented. The onset of the molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD, so early diagnosis of PD and adequate tracking of disease progression could significantly improve outcomes for patients. Because the clinical diagnosis of PD is challenging, misdiagnosis is common, which highlights the need for disease-specific and early-stage biomarkers. This review article aims to summarize useful biomarkers for the diagnosis of PD, as well as the biomarkers used to monitor disease progression. This review article describes the role of α-Syn in PD and how it could potentially be used as a biomarker for PD. Also, preclinical and clinical investigations encompassing genetics, immunology, fluid and tissue, imaging, as well as neurophysiology biomarkers are discussed. Knowledge of the novel biomarkers for preclinical detection and clinical evaluation will contribute to a deeper understanding of the disease mechanism, which should more effectively guide clinical applications.

Clinical Relevance of [18F]Florbetaben and [18F]FDG PET/CT Imaging on the Management of Patients with Dementia

PET of β-Amyloid plaques (Aβ) using [¹⁸F]florbetaben ([¹⁸F]FBB) and [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) increasingly aid clinicians in early diagnosis of dementia, including Alzheimer’s disease (AD), frontotemporal disease, dementia with Lewy bodies, and vascular dementia. The aim of this retrospective analysis was to evaluate clinical relevance of [¹⁸F]FBB, [¹⁸F]FDG PET and complimentary CSF measurements in patients with suspected dementia. In this study, 40 patients with clinically suspected or history of dementia underwent (1) measurement of Aβ peptides, total tau, and p-tau protein levels in the cerebrospinal fluid (CSF) compared with healthy controls (HC); (2) clinical and neuropsychological assessment, which included Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological assessment battery (CERAD-NAB); (3) [¹⁸F]FBB and [¹⁸F]FDG PET imaging within an average of 3 weeks. The subjects were within 15 days stratified using PET, CSF measurements as HC, mild cognitive impaired (MCI) and dementia including Alzheimer´s disease. The predictive dementia-related cognitive decline values were supporting the measurements. PET images were evaluated visually and quantitatively using standard uptake value ratios (SUVR). Twenty-one (52.5%) subjects were amyloid-positive (Aβ+), with a median neocortical SUVR of 1.80 for AD versus 1.20 relative to the respective 19 (47.5 %) amyloid-negative (Aβ-) subjects. Moreover, the [¹⁸F]FDG and [¹⁸F]FBB confirmed within a sub-group of 10 patients a good complimentary role by correlation between amyloid pathology and brain glucose metabolism in 8 out of 10 subjects. The results suggest the clinical relevance for [¹⁸F]FBB combined with [¹⁸F]FDG PET retention and CFS measurements serving the management of our patients with dementia. Therefore, [¹⁸F]FBB combined with [¹⁸F]FDG PET is a helpful tool for differential diagnosis, and supports the patients’ management as well as treatment.

Recent advances in enzymeless-based electrochemical sensors to diagnose neurodegenerative diseases

The use of sensitive electrochemical sensors to detect biomarkers is an effective method for the early diagnosis of several neurodegenerative diseases (NDs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, etc. However, the commercialization of enzyme/aptamer-based sensors is still hampered owing to the historic drawbacks of biorecognition elements including high cost, poor stability, and complex integration technology. Non-enzymatic electrochemical sensors are more attractive compared to their traditional counterparts and can be widely harnessed owing to their low cost, high stability, sensitivity, and ease of miniaturization. This review summarizes recent research progress focusing on the construction of non-enzymatic electrochemical sensors and analyzes their present use in the early diagnosis of NDs. Additionally, this review addresses the limitations and challenges of the use of current non-enzymatic electrochemical sensor technologies for the diagnosis of NDs and highlights the possible directions for future research.

Schisandrin Inhibits NLRP1 Inflammasome-Mediated Neuronal Pyroptosis in Mouse Models of Alzheimer's Disease

BACKGROUND

In recent years, schisandrin (SCH) was proved to improve Alzheimer's Disease (AD). The aim of our study is to explore the effect of SCH on neuronal pyroptosis in the disease.

METHODS

A Morris water maze test was performed to evaluate the spatial learning and memory retention of AD mouse. ELISA was fulfilled to examine the concentration of Aβ, IL-1β, and IL-18. Western blot was performed to detect the expression of apoptosis- and pyroptosis-related proteins. Besides, the neuronal apoptosis rate was examined using TUNEL assay. Immunohistochemistry was utilized to detect the activation of NLRP1 inflammasome.

RESULTS

Here, AD mice have serious cognitive impairment. Meantime, Aβ was highly expressed in the brains of AD mice. SCH could effectively rescue the cognitive impairment in AD mice and impede the production of Aβ. Subsequently, we further demonstrated that SCH repressed neuronal apoptosis, pyroptosis-related proteins expression, and the activation of NLRP1 inflammasome in the hippocampus of AD mice. We also proved that Aβ induced neuronal apoptosis and pyroptosis in vitro. However, the effects of Aβ on neuronal apoptosis and pyroptosis were partly reversed by SCH treatment.

CONCLUSION

Overall, our data indicated that SCH improved cognitive impairment in AD mice through inhibition of NLRP1 inflammasome-mediated neuronal pyroptosis and neuronal apoptosis. Our works provided new evidence to support SCH acting as a potential treatment method in AD.

Neuronal correlates of the visual-spatial processing measured with functional near-infrared spectroscopy in healthy elderly individuals

Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are a globally rising issue. It is necessary to detect such diseases early to find strategies for prevention. Typically, patients with MCI or AD show deviant neuronal patterns, which could be detected early through brain imaging techniques enabling assumptions about pre-existing diseases. Functional Near-Infrared Spectroscopy (fNIRS) is an appropriate imaging method because of its easy and economical nature with hardly any drawbacks. An early measurable risk factor indicating neurodegenerative processes could be a deficit in visual-spatial processing, which is localized in the parietal cortex. In this study, we aimed to measure the hemodynamic response of the visual-spatial processing in the healthy elderly participants of our long-term Vogel Study with fNIRS during the clock-hand-angle-discrimination task (ADT) to deepen our understanding of healthy brain mechanisms. Our results revealed for our healthy sample a significantly increased neuronal brain activity with increasing task difficulties, namely from the long to the middle to the short clock hand during ADT and significantly higher activation in the right hemisphere compared to the left hemisphere as well as in the superior parietal cortex compared to the inferior parietal cortex. Additionally, our behavioral data demonstrated longer reaction times and more errors with an increasing task requirement. We, therefore, assume that visual-spatial processing can successfully be operationalized with fNIRS for healthy elderly people based on ADT. Further fNIRS analyses are planned to investigate pathological neuronal correlates of visual-spatial function in MCI or AD study participants.

Education and Cognitive Decline: An Integrative Analysis of Global Longitudinal Studies of Cognitive Aging

BACKGROUND

The objective of this study was to examine the association between education and incidence of accelerated cognitive decline.

METHODS

Secondary analyses of data from the Health and Retirement Study (HRS), a nationally representative prospective cohort study of U.S. residents were conducted (N = 28,417). Cox proportional hazards survival models were layered on longitudinal mixed-effects modeling to jointly examine healthy cognitive aging and incidence of accelerated cognitive decline consistent with patterns seen in preclinical Alzheimer's disease and related dementias (ADRD). Replication analyses were completed on a database including 62,485 additional respondents from HRS sister studies. Life expectancy ratios (LER) and 95% confidence intervals (CIs) were reported.

RESULTS

This study replicated research showing that education was positively associated with cognition at baseline. Model fit improved using the survival method compared to random-slopes models alone. Analyses of HRS data revealed that higher education was associated with delayed onset of accelerated cognitive decline (LER = 1.031 95% CI = [1.013-1.015], p < 1E-06). Replication analyses using data from 14 countries identified similar results.

CONCLUSIONS

These results are consistent with cognitive reserve theory, suggesting that education reduces risk of ADRD-pattern cognitive decline. Follow-up work should seek to differentiate specific dementia types involved and consider potential mechanisms.

Purine molecules in Parkinson's disease: Analytical techniques and clinical implications

Parkinson's disease (PD) is a neurodegenerative disorder that primarily affects patients over the age of 65. PD is characterized by loss of neurons in the substantia nigra and dopamine deficiency in the striatum. Once PD is clinically diagnosed by the observation of motor dysfunction, the disease is already in its advance stages. Consequently, there is a major push to identify clinical biomarkers that are useful for the earlier detection of PD. Using untargeted metabolomics, several research groups have identified purine molecules, and specifically urate, as important biomarkers related to PD. This review will summarize recent findings in the field of purine metabolomics and biomarker identification for PD, including in the areas of PD pathophysiology, diagnosis, prognosis and treatment. In addition, this article will summarize and examine the primary research techniques that are employed to quantify purine molecules in both experimental systems and human subjects.

Microglial Sirtuin 2 Shapes Long-Term Potentiation in Hippocampal Slices

Microglial cells have emerged as crucial players in synaptic plasticity during development and adulthood, and also in neurodegenerative and neuroinflammatory conditions. Here we found that decreased levels of Sirtuin 2 (Sirt2) deacetylase in microglia affects hippocampal synaptic plasticity under inflammatory conditions. The results show that long-term potentiation (LTP) magnitude recorded from hippocampal slices of wild type mice does not differ between those exposed to lipopolysaccharide (LPS), a pro-inflammatory stimulus, or BSA. However, LTP recorded from hippocampal slices of microglial-specific Sirt2 deficient (Sirt2^–) mice was significantly impaired by LPS. Importantly, LTP values were restored by memantine, an antagonist of N-methyl-D-aspartate (NMDA) receptors. These results indicate that microglial Sirt2 prevents NMDA-mediated excitotoxicity in hippocampal slices in response to an inflammatory signal such as LPS. Overall, our data suggest a key-protective role for microglial Sirt2 in mnesic deficits associated with neuroinflammation.

Complementarity of gluCEST and 1 H-MRS for the study of mouse models of Huntington's disease

Identification of relevant biomarkers is fundamental to understand biological processes of neurodegenerative diseases and to evaluate therapeutic efficacy. Atrophy of brain structures has been proposed as a biomarker, but it provides little information about biochemical events related to the disease. Here, we propose to identify early and relevant biomarkers by combining biological specificity provided by ¹ H-MRS and high spatial resolution offered by gluCEST imaging. For this, two different genetic mouse models of Huntington's disease (HD)-the Ki140CAG model, characterized by a slow progression of the disease, and the R6/1 model, which mimics the juvenile form of HD-were used. Animals were scanned at 11.7 T using a protocol combining ¹ H-MRS and gluCEST imaging. We measured a significant decrease in levels of N-acetyl-aspartate, a metabolite mainly located in the neuronal compartment, in HD animals, and the decrease seemed to be correlated with disease severity. In addition, variations of tNAA levels were correlated with striatal volumes in both models. Significant variations of glutamate levels were also observed in Ki140CAG but not in R6/1 mice. Thanks to its high resolution, gluCEST provided complementary insights, and we highlighted alterations in small brain regions such as the corpus callosum in Ki140CAG mice, whereas the glutamate level was unchanged in the whole brain of R6/1 mice. In this study, we showed that ¹ H-MRS can provide key information about biological processes occurring in vivo but was limited by the spatial resolution. On the other hand, gluCEST may finely point to alterations in unexpected brain regions, but it can also be blind to disease processes when glutamate levels are preserved. This highlights in a practical context the complementarity of the two methods to study animal models of neurodegenerative diseases and to identify relevant biomarkers.

On-Chip Detection of the Biomarkers for Neurodegenerative Diseases: Technologies and Prospects

Alzheimer's disease (AD), Parkinson's disease (PD) and glaucoma are all regarded as neurodegenerative diseases (neuro-DDs) because these diseases are highly related to the degeneration loss of functions and death of neurons with aging. The conventional diagnostic methods such as neuroimaging for these diseases are not only expensive but also time-consuming, resulting in significant financial burdens for patients and public health challenge for nations around the world. Hence early detection of neuro-DDs in a cost-effective and rapid manner is critically needed. For the past decades, some chip-based detection technologies have been developed to address this challenge, showing great potential in achieving point-of-care (POC) diagnostics of neuro-DDs. In this review, chip-based detection of neuro-DDs' biomarkers enabled by different transducing mechanisms is evaluated.

Deep Learning Identifies Digital Biomarkers for Self-Reported Parkinson's Disease

Large-scale population screening and in-home monitoring for patients with Parkinson's disease (PD) has so far been mainly carried out by traditional healthcare methods and systems. Development of mobile health may provide an independent, future method to detect PD. Current PD detection algorithms will benefit from better generalizability with data collected in real-world situations. In this paper, we report the top-performing smartphone-based method in the recent DREAM Parkinson's Disease Digital Biomarker Challenge for digital diagnosis of PD. Utilizing real-world accelerometer records, this approach differentiated PD from control subjects with an area under the receiver-operating characteristic curve of 0.87 by 3D augmentation of accelerometer records, a significant improvement over other state-of-the-art methods. This study paves the way for future at-home screening of PD and other neurodegenerative conditions affecting movement.

T1-weighted MRI-driven Brain Age Estimation in Alzheimer's Disease and Parkinson's Disease

Neuroimaging-driven brain age estimation has introduced a robust (reliable and heritable) biomarker for detecting and monitoring neurodegenerative diseases. Here, we computed and compared brain age in Alzheimer's disease (AD) and Parkinson's disease (PD) patients using an advanced machine learning procedure involving T1-weighted MRI scans and gray matter (GM) and white matter (WM) models. Brain age estimation frameworks were built using 839 healthy individuals and then the brain estimated age difference (Brain-EAD: chronological age subtracted from brain estimated age) was assessed in a large sample of PD patients (n = 160) and AD patients (n = 129), respectively. The mean Brain-EADs for GM were +9.29 ± 6.43 years for AD patients versus +1.50 ± 6.03 years for PD patients. For WM, the mean Brain-EADs were +8.85 ± 6.62 years for AD patients versus +2.47 ± 5.85 years for PD patients. In addition, PD patients showed a significantly higher WM Brain-EAD than GM Brain-EAD. In a direct comparison between PD and AD patients, we observed significantly higher Brain-EAD values in AD patients for both GM and WM. A comparison of the Brain-EAD between PD and AD patients revealed that AD patients may have a significantly "older-appearing" brain than PD patients.